With the proliferation of networked computing, many computing tasks are increasingly being handled at remote computing resources such as cloud-based services. Datacenters housing a multitude of servers and other specialized computing devices provide businesses with a range of solutions for systems deployment and operation. New technologies and practices are designed to handle the scale and the operational requirements of such large-scale operations. These practices eventually migrate toward private data centers, and are adopted largely because of their practical results.
Managing a datacenter depends on performing datacenter management tasks across multiple technologies across multiple datacenter servers. Challenges with datacenter management include the fact that high number of technologies employed in a typical datacenter may require resources knowledgeable about each technology and the high number of servers employed in a typical datacenter may require that management tasks be employed against many servers. A task that is trivial to perform against one server may quickly become non-trivial when it must be performed against multiple servers at a time. Management tasks often cross technology silos, resulting in even greater complexity as organizational boundaries necessitate that multiple participants be employed in the completion of the task.
Furthermore, a resource that performs a task across one or more technologies may often require broad permissions to perform the task, making the principle of least privilege difficult to employ without requiring that a task involve multiple participants—each with their own limited scope of access per datacenter technology, resource, or server. Moreover, datacenter tasks are not necessarily evenly distributed per technology or server, making resource allocation difficult while minimizing scope of access. In addition, resources with the knowledge to perform tasks across multiple technologies are typically more expensive and difficult to acquire.